Search: “framework”

arXiv:2609.30517v1 Announce Type: cross Abstract: Recent progress in speech-driven 3D facial animation has improved vertex-level reconstruction quality, but speech-consistent visible articulation rema

applicationsarxiv-cs-lg

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Agents

Segment-Level Agentic Topic Modeling for Improved Data Exploration and Resource Efficiency

DGX agent

arXiv:2609.31460v1 Announce Type: new Abstract: Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a var

agentsarxiv-cs-ai

28 Sept 2026

Hardware

Selective Amortization of Full-Budget Counterfactual Reasoning for Visual Token Communication

arXiv:2609.30756v1 Announce Type: new Abstract: Generative image communication transmits compact semantic tokens under a limited packet budget, where token selection directly affects the final reconst

hardwarearxiv-cs-ai

Self-Play Search Distillation for Large Language Model Reasoning

arXiv:2609.30936v1 Announce Type: new Abstract: Improving reasoning abilities in Large Language Models (LLMs) requires high-quality data that exposes difficult decisions, competing alternatives, and t

researcharxiv-cs-ai

Self-Supervised Perceptually Interpretable Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2609.30987v1 Announce Type: new Abstract: Self-supervised monocular depth estimation (MDE) enables depth prediction from monocular images without requiring ground-truth supervision, making it at

Semantic Navigation for Issue Localization in Code Repository

arXiv:2609.31176v1 Announce Type: new Abstract: Repository-level issue localization aims to identify and rank the files and functions relevant to resolving a reported issue. LLM agents approach this t

SoGuDiff: Socially Guided Diffusion for Steerable, Norm-Grounded Robot Navigation

arXiv:2609.30560v1 Announce Type: new Abstract: Beyond collision avoidance, socially competent robot navigation requires adherence to implicit social conventions that vary across contexts, cultures, a

tutorialsarxiv-cs-ro

Spatial Information Bottleneck for Interpretable Visual Recognition

arXiv:2511.09239v2 Announce Type: replace Abstract: Deep neural networks typically learn spatially entangled representations that conflate discriminative foreground features with spurious background c

tutorialsarxiv-cs-cv

SPO: Discovering Adaptive Large Neighborhood Search Operators via Stackelberg Program Optimization

arXiv:2609.31179v1 Announce Type: new Abstract: Large neighborhood search (LNS) relies critically on destroy and repair operators, whose effectiveness depends on both adaptation to the evolving LNS st

Staged Depth Training: A Representation Curriculum for PINNs

arXiv:2609.30299v1 Announce Type: new Abstract: Representation quality is a central determinant of PINNs' performance, yet standard training leaves representations to emerge implicitly while fitting t

local-aiarxiv-cs-lg

Stealth Apart, Harm Together: Skill Cascading Attacks on Skill-Based Agent Systems

arXiv:2609.30383v1 Announce Type: new Abstract: A skill is a modular package of natural-language instructions, executable scripts, and reference resources that an agent can load at runtime to extend i

StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction

arXiv:2605.06642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon decision making remains difficu

Structure-Guided Masked Autoencoders for Ultra-High Resolution Scientific Image Understanding

arXiv:2609.30682v1 Announce Type: new Abstract: Self-supervised pre-training with Vision Transformers, including Masked Autoencoders (MAE), is difficult to apply to gigapixel scientific images. Random

tutorialsarxiv-cs-cv

Applications

TaskIR: Task-Driven Image Restoration via Degradation Adaptation and Task Feedback

arXiv:2609.31170v1 Announce Type: new Abstract: Task-driven image restoration aims to improve both image quality and downstream task performance. However, existing methods predominantly focus on singl

applicationsarxiv-cs-cv

The N-5 Scaling Law: Topological Dimensionality Reduction in the Optimal Design of Fully-actuated Multirotors

arXiv:2512.23619v3 Announce Type: replace Abstract: We investigate the topological structure of the optimal actuation landscape for fully-actuated N-rotor aerial vehicles. By formulating the design pr

researcharxiv-cs-ro

Timo: extbf{T}aming Multextbf{i}modal Diffusion Transformer for Human extbf{Mo}tion Generation

model-releasesarxiv-cs-cv

arXiv:2609.30761v1 Announce Type: new Abstract: Most existing human motion generation (HMG) methods use cross-attention modules to inject text semantics, but ignore the importance of bidirectional mod

TISD: On-Policy Self-Distillation with Trajectory Intervention

arXiv:2609.30878v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) provides dense teacher targets, but evaluates them only along student-sampled rollouts. When the privileged teacher f

safetyarxiv-cs-ai

ToolSearcher: Optimizing Tool Selection at Scale via Reinforcement Learning

arXiv:2609.30906v1 Announce Type: new Abstract: Large language models (LLMs) excel at natural language processing but struggle to interact with external environments. Tool learning provides a promisin

agentsarxiv-cs-cl

Toward AI-Augmented Cooperative Engineering Workflows: Requirements and Architecture the European Rover Challenge

arXiv:2609.31136v1 Announce Type: new Abstract: The growing availability of Artificial Intelligence (AI) tools creates new opportunities to support engineering design processes, yet their current use

researcharxiv-cs-ai

Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learning

arXiv:2609.31376v1 Announce Type: cross Abstract: Congenital heart disease (CHD) is the most common birth defect, yet a large fraction of cases remain undetected on prenatal ultrasound, in part becaus

researcharxiv-cs-cv

TR-SSQP: A Trust-Region Method for Constrained Stochastic Optimization under Heavy-Tailed Noise

model-releasesarxiv-cs-lg

arXiv:2609.30732v1 Announce Type: cross Abstract: We consider stochastic nonlinear optimization problems with deterministic equality constraints. While unconstrained stochastic optimization is well un

TRACE: Temporal Audit and Condition-aware Evaluation of Streaming Video Understanding

model-releasesarxiv-cs-cl

arXiv:2609.30670v1 Announce Type: new Abstract: Streaming video understanding requires models to interpret evidence as it arrives, yet current evaluations often report task scores without specifying w

Transformer-based Monte Carlo Localization in Construction Meshes

arXiv:2609.31357v1 Announce Type: new Abstract: To be able to perform inspection or digitization tasks, mobile robots on construction sites must be able to localize themselves reliably with respect to

local-aiarxiv-cs-ro

UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification

arXiv:2605.06221v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance rapidly, they are becoming increasingly capable while simultaneously demanding ever-longer conte

researcharxiv-cs-cl

User Model Extraction via Belief Self-Distillation

arXiv:2609.31603v1 Announce Type: cross Abstract: Large language models (LLMs) implicitly infer attributes of their users and adapt their behavior accordingly, yet these beliefs remain difficult to in

safetyarxiv-cs-cl

VisTacAlign: Co-Training Dexterous Policies on Tactile Human and Robot Demonstrations

arXiv:2609.30959v1 Announce Type: new Abstract: Human demonstrations are a cheap source of data for dexterous manipulation, but co-training a robot policy on them requires closing the human--robot gap

safetyarxiv-cs-ro

VLALight: Lightweight Vision-Language-Action Models for Emergency-Aware Traffic Signal Control

arXiv:2609.30709v1 Announce Type: cross Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretati

When Is a Multi-Agent Code Judge Actually Grounded? Two Label-Free Measurements, and a Judge That Declines to Guess

arXiv:2609.30328v1 Announce Type: new Abstract: When one language model judges whether another's code is correct, it does not report the absence of evidence. It returns a confident verdict with reason

WorldTS: World Modeling for Multimodal Covariate-aware Time Series Forecasting

arXiv:2609.31162v1 Announce Type: new Abstract: Time series forecasting is typically framed as learning a direct mapping from historical to future observations in the observation space. However, seque

tutorialsarxiv-cs-lg

A Hybrid CNN--State-Space--Attention Backbone with Joint-Embedding Predictive Pretraining for 12-Lead ECG Classification

model-releasesarxiv-cs-cv

arXiv:2609.29376v1 Announce Type: new Abstract: Automatic 12-lead electrocardiogram (ECG) classification requires representations that jointly capture local waveform morphology, long-range temporal dy

A Living Benchmark for Information Retrieval from Electronic Health Records

arXiv:2609.30205v1 Announce Type: new Abstract: Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how cli

A Manifold-Aware Topic Modeling Approach via Rank-Based Prototypes

arXiv:2609.29630v1 Announce Type: cross Abstract: Recent topic models leverage pretrained embeddings, but neural architectures produce latent representations without grounding in specific texts, and c

researcharxiv-cs-ai

A Rapid Pipeline for Training and Deploying ML Models on WeBe Band

arXiv:2609.29084v1 Announce Type: new Abstract: Developing optimized machine-learning algorithms for edge devices with limited computational and memory resources is challenging, time-consuming, and hi

local-aiarxiv-cs-ai

A Wrong Turn Does Not Ruin the Journey: Deviation-Guided Skill Self-Evolution for LLM Agents

arXiv:2609.29154v1 Announce Type: new Abstract: Large language model agents increasingly rely on natural-language skills to solve complex tool-use tasks. However, such tasks often admit multiple valid

ADM-Planner: LLM-Guided Long-Horizon Planning for Mobile Manipulators with Attention-Enhanced Dynamic Memory

model-releasesarxiv-cs-ro

arXiv:2609.29212v1 Announce Type: new Abstract: Large language models can decompose mobile-manipulation goals into long action sequences, but the resulting plans remain reliable only while their world

Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems

arXiv:2609.30001v1 Announce Type: new Abstract: Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model,

Adversarial Closed-Loop Curriculum for Evolving Role-Playing Agents

arXiv:2609.28609v1 Announce Type: new Abstract: Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL me

AgentKernel: The Trust-Native Agentic Operating System

arXiv:2609.29647v1 Announce Type: cross Abstract: Modern AI agents routinely cross trust boundaries: they ingest untrusted content, combine it with privileged instructions, persist intermediate belief

AgriCountDINO: Parameter-Efficient Exemplar-Guided Counting and Localization in Agriculture

arXiv:2609.29460v1 Announce Type: cross Abstract: Accurate counting and localization of plants and their organs support phenotyping and yield estimation, yet target appearance, scale, and density vary

AlphaDiverse: Post-Training Local Quantitative Research Agents for Diverse Exploration in Alpha Factor Mining

arXiv:2609.29014v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems can automate alpha factor mining, but their reliance on external APIs limits control over cost, ava

local-aiarxiv-cs-ai

An Analysis of Streaming Deep Reinforcement Learning for Adaptive Continual Learning in Robotics

arXiv:2609.28807v1 Announce Type: new Abstract: Over the course of a lifetime, robots may encounter novel scenarios unaccounted for in its original training that result in performance degradation. One

safetyarxiv-cs-ro

An Analytical Theory of Auxiliary Learning

arXiv:2609.29774v1 Announce Type: new Abstract: Auxiliary learning is an optimization paradigm in which a neural network's performance on a target task is improved by jointly training it on additional

researcharxiv-cs-lg

Anatomy-Aligned Surface Field Learning for Myocardial Reconstruction from Sparse Short-Axis Cine MRI

arXiv:2609.29825v1 Announce Type: new Abstract: Patient-specific 4D myocardial reconstruction from cine MRI supports quantitative functional assessment, regional motion analysis, and simulation-based

researcharxiv-cs-cv

Anatomy-aware cross-speaker adaptation of complete vocal-tract acoustic-to-articulatory inversion

arXiv:2609.29766v1 Announce Type: cross Abstract: Cross-speaker acoustic-to-articulatory inversion requires accounting for anatomical differences between speakers. We propose a geometric adaptation fr

safetyarxiv-cs-ai

Assessing the Impact of Fleet Size on Crowdsourced Mapping Using a Dissimilarity Measure

arXiv:2609.29198v1 Announce Type: new Abstract: Accurate digital maps are essential for Advanced Driver Assistance Systems (ADAS) or Autonomous Driving (AD), providing critical information such as roa

safetyarxiv-cs-ro

AV-GRPO: Modality-Anchored Decoupling Diffusion Reinforcement Learning for Joint Audio-Video Generation

arXiv:2609.29816v1 Announce Type: new Abstract: Recent years have witnessed major progress in joint audio-video generation. Existing models still suffer from limited per-modality fidelity, insufficien

safetyarxiv-cs-cv

Back to the Definition: Estimating Step-Level Advantages via Trajectory Graphs for Agentic Reinforcement Learning

arXiv:2609.28963v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) methods, such as GRPO and its variants, have become a leading paradigm for training reasoning and agentic large

safetyarxiv-cs-ai

Band-Attention Modulation Network for Robust Face Forgery Detection

arXiv:2404.06022v3 Announce Type: replace-cross Abstract: Face forgery detection faces critical challenges in generalizing to unseen manipulation techniques and remaining robust under image compressio

tutorialsarxiv-cs-ai